BS degree in Data Science Analytics

Looking to earn a BS degree (perhaps a second one!) that will attract the attention of employers?

Earn a Bachelor of Science (BS) degree from Thomas Edison State University's Heavin School of Arts and Sciences (TESU) through a curricular partnership withThe Institute for Statistics Education at Statistics.com.

The data science component (area of study - both core and electives) is taught online at Statistics.com. The General Education and Electives required by the program are completed via online courses and other credit earning options offered by TESU. TESU specializes in awarding credit for demonstrated college-level competencies. You may be able to earn substantial credit award based on your prior learning and colege-level expertise.

Planning my Program

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In this certificate program, there are '8' required courses + you choose '4' electives

FULL PROGRAM LIST

Required Courses (8)

Forecasting Analytics

This course will teach you how to choose an appropriate time series model, fit the model, to conduct diagnostics, and use the model for forecasting.
Next three dates:

March 23, 2018 to April 20, 2018July 27, 2018 to August 24, 2018November 23, 2018 to December 21, 2018

The course introduces the use of mathematical models for managerial decision making and covers how to formulate linear programming models for decision problems where multiple decisions need to be made in the best possible way while simultaneously satisfying a number of logical conditions (or constraints). You will learn how to use spreadsheet software to implement and solve these linear programming problems.
Next three dates:

This course covers the two core paradigms that account for most business applications of predictive modeling: classification and prediction. The course includes hands-on work with XLMiner, a data-mining add-in for Excel.
Next three dates:

May 25, 2018 to June 22, 2018September 28, 2018 to October 26, 2018May 22, 2020 to June 21, 2020

This course covers the two core paradigms that account for most business applications of predictive modeling: classification and prediction. The course includes hands-on work with XLMiner, a data-mining add-in for Excel.
Next three dates:

February 23, 2018 to March 23, 2018June 29, 2018 to July 27, 2018October 26, 2018 to November 23, 2018

This course covers key unsupervised learning techniques - association rules, principal components analysis, and clustering. The course will include an integration of supervised and unsupervised learning techniques.
Next three dates:

This course covers a number of advanced topics in optimization. You will learn: 1) how to formulate and solve network flow problems, 2) how to model and solve optimization problems where some or all of the decision variables must be integers, 3) how to deal with multiple objectives in optimization problems, and 4) techniques for handling optimization problems where the objective function or constraints are not linear functions of the decision variables.
Next three dates:

In this course you'll learn basic Python skills and data structures, move on to how to load data from different sources, rearrange and aggregate it, and finally how to analyze and visualize it to create high-quality products.
Next three dates:

In this course you will learn how multiple linear regression models are derived, use software to implement them, learn what assumptions underlie the models, learn how to test whether your data meet those assumptions and what can be done when those assumptions are not met, and develop strategies for building and understanding useful models.
Next three dates:

Spatial statistical analysis uses methods adapted from conventional statistics to address problems in which spatial location is the most important explanatory variable. This course will explain and give examples of the analysis that can be conducted in a geographic information system such as ArcGIS or Mapinfo.
Next three dates:

The purpose of this course is to teach you how to extract data from a relational database using SQL, and merge it into a single file in R, so that you can perform statistical operations.
Next three dates:

March 16, 2018 to April 13, 2018August 03, 2018 to August 31, 2018November 09, 2018 to December 07, 2018

The above estimate includes the program registration fee, and individual course fees. It reflects considerable savings that are available if you pay the program cost upon enrollment. You also have the option of paying in monthly installments, or on a course-by-course basis:

This "pay-as-you-go" estimate includes the application fee, the registration fee, individual course fees that you pay as you progress through the program, as well as various tuition savings available to you once you are a matriculated certificate candidate at the Institute. The actual total cost of the program may vary slightly depending on several factors and may differ slightly from the estimate above; fees are subject to change without prior notice.

You get considerable savings if you:

Pay up front: $5000*

Pay in installments: $290/month*

*Includes registration fee, but not application fee of $

Who is this program for?

This program is aimed at working adults who want to learn to use the tools and problem-solving skills of statistics and analytics in the rapidly growing field of data science.

Cost for the data science courses from Statistics.com

$5,700 pay in full$5,825 installment$5,950 pay as you enroll

*does not include the cost of text or materials per course

Admission process

Students need to apply directly to TESU to be admitted into the BS program, however, the Statistics.com courses may be taken before admission to TESU, provided that these students adhere to the ACE standards in their Statistics.com courses.

Transfer your Statistics.com course to TESU

Thomas Edison State University accepts the credit recommendations of the American Council on Education (ACE) CREDIT. All the courses listed in this program have been recommended for ACE CREDIT.

Register online at Statistics.com for the courses in this program

When the course begins, you will specify your marking preference- choose "I will be seeking academic credit recommendation through ACE and I am a student at TESU."